This survey focuses on critical role of machine learning in developing Human Activity Recognition applications based on inertial sensors in conjunction with physiological and environmental sensors.
The first ever study to use urinary cellular gene expression to study sepsis. Researchers identified alterations in gene expression unique to systemic and kidney-specific pathophysiologic processes using whole-genome analyses of RNA isolated from the urinary cells of sepsis patients.
Among critically ill surgical sepsis patients, persistent AKI and the absence of renal recovery are associated with distinct early and sustained immunologic and endothelial biomarker signatures and decreased long-term physical function and survival.
Audiovisual modules may improve knowledge and comprehension of commonly performed ICU procedures among critically ill patients and caregivers who have no healthcare background.
In this paper, the problem of mining complex temporal patterns in the context of multivariate time series is considered. A new method called the Fast Temporal Pattern Mining with Extended Vertical Lists.
Patients and physicians make essential decisions regarding diagnostic and therapeutic interventions. These actions should be performed or deferred under time constraints and uncertainty regarding patients’ diagnoses and predicted response to treatment. This may lead to cognitive and judgment errors.
As AI continues to transform healthcare, it is crucial to address the technical, ethical, and social challenges that arise. AI is evolving from a mere tool to an assistant, and potentially a colleague. Likewise, AI must adhere to the same ethical standards colleagues follow to ensure credibility and trust remains. Our literature review, led by Maurizio Cecconi, explores the importance of data standardization, real-time ICU networks, and education in integrating AI into acute medicine. By focusing on these areas, we aim to enhance patient outcomes and strengthen the trust between healthcare providers and patients. Join us in advancing responsible AI practices that uphold integrity in clinical settings.
Intraoperative hypotension (IOH) is tied to costly postoperative complications, including acute kidney injury (AKI). Better IOH control in non-cardiac surgeries alone could reduce postoperative costs by $1.6 million annually for hospitals with 10,000 patients.
Despite its effectiveness, there is no clean consensus on safe intraoperative blood pressure levels that protect against AKI, leaving clinicals without standardized guidelines for managing hypotension during surgery.
Our latest research delves into defining IOH thresholds to mitigate AKI risks, aiming to guide safer and more cost-effective surgical practices.
